A New Approach to Hazardous Materials Transportation Risk Analysis: Decision Modeling to Identify Critical Variables

We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity , and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.     

Energy modeling as a tool for planning

This paper discusses the application of a general equilibrium model, developed at Stanford Research Institute, for use in long range forecasting and business planning. The value of the modeling approach is illustrated through application to a hypothetical natural gas liquefaction venture. Specific features and representative output of the SRI model are presented. The authors stress the use of a modeling approach in the planning process as a quantitative means of evaluating the importance of uncertainty in specific decision variables and the ability of such model to test explicitly the long term impact of changes in a given set of base assumptions.     

基于核心制造规范的外包决策模型及实证研究

本文将制造规范概念引入外包决策,从考虑企业长期绩效和长期竞争力的角度提出了一个以制造规范核心度和流失度为控制变量的二维外包决策模型。决策模型将外包环境分为九种类型,涵盖了从内部制造、各种形式的外包,到简单采购等所有"买或做"的决策,尤其是对介于自制与简单采购之间灰色地带的外包,给出了考虑提供制造规范主体和供应商类型的不同类型合作和联盟治理结构策略。对四个不同类型的企业典型产品近1000个零件的外包决策进行了统计分析,实证了模型的有效性。模型对现实世界观察到的制造企业由于没有按照其中规律行事而导致失败的原因做出了合理而明确解释。     

复杂决策问题的多元化模型体系研究

鉴于复杂决策问题的特点,仅仅依靠定量模型难以描述和求解复杂决策问题. 从定性到 定量综合集成角度出发,认为复杂决策问题的求解过程需要多元化模型支持. 依据复杂决策问 题的认知层次,提出复杂决策问题的多元化模型体系中包含概念模型、结构模型和数学模型, 并对这三类模型进行了论述.     

The Risk Criteria for Assessment of Temporary Changes in a Nuclear Power Plant

Risk criterion is a term that may distinguish between what is considered as an acceptable level of safety and what is not. One of the ways of determining quantitative risk criteria for temporary changes in a nuclear power plant considering probabilistic safety assessment is presented. Risk criteria are based on timing and on time duration of the change. Several examples of temporary changes in a nuclear power plant were examined to evaluate the criteria. Results show that it is possible to determine a set of risk criteria for temporary changes. Risk criteria can represent a standpoint for risk-informed decision making.     

基于碳标签制度的两级供应链协调机制研究

以市场需求随机的视角建立Stackelberg博弈模型,研究基于碳标签制度的供应商和零售商组成的两级供应链协调策略。模型引入产品碳足迹e₁作为决策变量,分别研究了在收益共享与成本共担契约下集中决策和分散决策中决策变量最优解及最优利润的变化情况。研究结果表明,在考虑碳排因素时集中决策相比于分散决策具有明显的优势;在参数满足一定条件下零售商通过与供应商共担碳减排成本,可以实现利润的增长,初步验证模型的契约设计的有效性。     

On the influence of a biased decision support model on subjects’ behavior

Summary  The role of decision tools in managerial decisions can be crucial. Yet, there is very little research seeking to understand and measure the influence of planning models on decision-makers’ actual behavior or performance. We focus on investigating, in an experimental context, the influence of a decision model (time allocation model) on student subjects’ changes of mind and behavior. Of special interest is the effect of the articulated importance of criteria on subjects’ choices. Furthermore, we have also studied how the above mentioned model influences subjects’ actual (measurable) performance. The results are partly conflicting, though interesting: (1) the (biased) decision model did have a significant influence on the subjects’ choices, (2) when the model provided additional freedom to improve criterion values, the subjects’ choices were rather inconsistent with the articulated importance of criteria, (3) the interpretation is not clear, how plans influence actual behavior, and (4) the subjects did not fully recognize the bias of the model (when present). However, our findings very clearly demonstrate that model developers have a great responsibility. Biased models may guide managers to make dramatically erroneous decisions in bona fide. We hope that our findings generate additional research into this important, but under-researched topic.      

Global supplier development considering risk factors using fuzzy extended AHP-based approach

Global supplier development is a multi-criterion decision problem which includes both qualitative and quantitative factors. The global supplier selection problem is more complex than domestic one and it needs more critical analysis. The aim of this paper is to identify and discuss some of the important and critical decision criteria including risk factors for the development of an efficient system for global supplier selection. Fuzzy extended analytic hierarchy process (FEAHP) based methodology will be discussed to tackle the different decision criteria like cost, quality, service performance and supplier's profile including the risk factors involved in the selection of global supplier in the current business scenario. FEAHP is an efficient tool to handle the fuzziness of the data involved in deciding the preferences of different decision variables. The linguistic level of comparisons produced by the customers and experts for each comparison are tapped in the form triangular fuzzy numbers to construct fuzzy pair-wise comparison matrices. The implementation of the system is demonstrated by a problem having four stages of hierarchy which contains different criteria and attributes at wider perspective. The proposed model can provide not only a framework for the organization to select the global supplier but also has the capability to deploy the organization's strategy to its supplier.     

Multi-time scale Markov decision process approach to strategic network growth of reverse supply chains

This paper addresses a complex set of decisions that surround the growth over time of reverse supply chain networks that collect used products for reuse, refurbishment, and/or recycling by processors. The collection network growth problem is decomposed into strategic, tactical and operational problems. This paper focuses on the strategic problem which is to determine how to allocate capital budget resource effectively to grow the network to meet long term collection targets and collection cost constraints. We model the strategic problem as a Markov decision process which can also be posed as multi-time scale Markov decision problem. The recruitment problem in a tactical level appears as a sub-problem for the strategic model. Using dynamic programming, linear programming and Q-Learning approaches, an heuristic is implemented to solve realistically sized problems. A numerical study demonstrates that the heuristic can obtain a good solution for the large-scale problem in reasonable time which is not possible when trying to obtain the optimal solution with the exact DP approach.     

Managing the Risk of Uncertain Threshold Responses: Comparison of Robust, Optimum, and Precautionary Approaches

Many commentators have suggested the need for new decision analysis approaches to better manage systems with deeply uncertain, poorly characterized risks. Most notably, policy challenges such as abrupt climate change involve potential nonlinear or threshold responses where both the triggering level and subsequent system response are poorly understood. This study uses a simple computer simulation model to compare several alternative frameworks for decision making under uncertainty -- optimal expected utility, the precautionary principle, and three different approaches to robust decision making -- for addressing the challenge of adding pollution to a lake without triggering unwanted and potentially irreversible eutrophication. The three robust decision approaches -- trading some optimal performance for less sensitivity to assumptions, satisficing over a wide range of futures, and keeping options open -- are found to identify similar strategies as the most robust choice. This study also suggests that these robust decision approaches offer a quantitative, decision analytic framework that captures the spirit of the precautionary principle while addressing some of its shortcomings. Finally, this study finds that robust strategies may be preferable to optimum strategies when the uncertainty is sufficiently deep and the set of alternative policy options is sufficiently rich.     

基于偏好决策的MC模式下供应链调度优化

分析了随机需求与随机资源约束条件下的MC模式下供应链调度过程中蕴含的主要矛盾问题,提出对供应链协作成员动态收益满意偏好的合理决策是有效解决矛盾的关键因素之一。对影响和决定该偏好的主、客观因素进行了界定以及定性与定量分析,建立了基于协作成员满意收益的利益偏好决策模型,最后将其引入MC模式下的供应链调度优化模型,通过算例分析,验证了思路与模型的有效性。     

Exploring Framing Effects in Inventory Control Decisions: Violations of Procedure Invariance

Recent research on decision framing has shown that (i) there are multiple types of framing effects and (ii) the context of the decision can influence framing effects. This research examines decision framing effects in inventory control contexts by questioning the assumption of procedure invariance, that preference should not be impacted by how options are presented to a supply chain manager making an inventory control decision. Study 1 uses three single‐shot decision experiments to establish that all three types of framing effects identified by Levin et al. ( 1998 ) apply in basic inventory control contexts. Results were consistent with theory in all three cases. Given this evidence that framing effects have potential to impact inventory control decisions, two laboratory experiments in Study 2 utilize multi‐period decision tasks to demonstrate that framing effects can impact performance in a dynamic inventory decision setting similar to practice. One of the experiments in Study 2 was conducted with student subjects, while the other with inventory managers from a large retail firm. Results from both experiments provide evidence that even when initial framing effects on order quantities fade, there can be longer term effects on inventory levels and performance. Furthermore, these effects are robust to education and professional experience. The findings suggest that although a manager might select appropriate inventory control metrics, prudence must be exercised in the presentation of these metrics, and that mere presentation can be used to alleviate known human biases in inventory control decisions.     

网络环境下消费者感知效用模型的构建与研究

商品效用的大小是消费者购买决策的出发点,论文以感知效用为视角,分析了网络消费者的非补偿性决策和补偿性决策,构建了网络消费者感知效用模型,并以此为基础,深入分析了信息收集成本、质量评估成本、商品价格以及购物风险等成本变量对网络购物环境下消费者感知效用的影响。研究结果表明,无论是风险规避型网络消费者,还是风险型网络消费者,商品质量的提高均可以增大消费者感知效用,而商品价格、购物风险的增大将导致消费者感知效用减小,但对于风险型网络消费者,由于承受风险能力强,商品价格的升高并没有增大消费者心理风险成本,而对于风险规避型网络消费者,随着商品价格的升高,消费者心理风险成本相应增大。     

多标准决策表中发现概率规则的变精度粗糙集方法

用优势关系代替不可分辨关系,本文提出了一种可以从多标准决策表中获取概率规则的扩展变精度粗糙集模型,该模型能够处理多标准决策表中可能的不一相容性,获取由偏好对象组成的概率决策规则集,并导出事例决策系统的偏好模型。研究结果表明:基于优势关系,从多标准决策表中获取的最小概率规则集,使用的条件数量较少,且导出规则的数量较少、较强。     

随机需求下单向替代的两产品订货与定价联合决策研究

考虑了存在单向替代的两产品订货和定价联合决策问题。通过构建订货与定价联合决策模型,研究了单周期两产品的最优订货量和价格的存在条件,进一步将研究拓展到多周期的情况,建立了多周期的订货和定价联合决策模型,并进行了模型结构分析。同时,分析了信息对订货与定价联合决策的影响程度。     

带有潜变量的结构方程模型在突发事件应急管理中的应用

如何使事件与机构挂钩是突发事件应急管理中的一个重要问题;通过带有潜变量的结构方程模型能够建立起事件与机构之间的定量联系,从而为进一步对机构作评价和制定考核标准提供依据。     

考虑背景风险的项目投资决策

在项目投资过程中不但面临项目风险,同时还面临背景风险,且背景风险与项目风险之间往往存在着一定的相关性。文章在已有研究的基础上,针对考虑背景风险的项目投资决策问题,分析了风险之间的相关性及相关程度对投资决策的影响。首先讨论了加性背景风险和乘性背景风险单独存在时,背景风险与项目风险之间的相关性对投资决策的影响;其次构建了两种背景风险同时存在情形下的投资模型,进而通过蒙特卡罗仿真方法给出不同相关程度下的仿真结果,在此基础上分析两种背景风险与项目风险之间的相关性及相关程度对投资决策的影响并给出相关研究结论。     

A Fuzzy Decision Tree for Fault Classification

In plant accident management, the control room operators are required to identify the causes of the accident, based on the different patterns of evolution of the monitored process variables thereby developing. This task is often quite challenging, given the large number of process parameters monitored and the intense emotional states under which it is performed. To aid the operators, various techniques of fault classification have been engineered. An important requirement for their practical application is the physical interpretability of the relationships among the process variables underpinning the fault classification. In this view, the present work propounds a fuzzy approach to fault classification, which relies on fuzzy if-then rules inferred from the clustering of available preclassified signal data, which are then organized in a logical and transparent decision tree structure. The advantages offered by the proposed approach are precisely that a transparent fault classification model is mined out of the signal data and that the underlying physical relationships among the process variables are easily interpretable as linguistic if-then rules that can be explicitly visualized in the decision tree structure. The approach is applied to a case study regarding the classification of simulated faults in the feedwater system of a boiling water reactor.     

MRPⅡ和独立有限调度的分析比较

MRPⅡ是当今制造业普遍采用的计算机辅助管理模式,但MRPⅡ的能力调度有一定的缺陷．本文论述了能力调度的新方法──独立有限调度,并通过图表模型详细分析这两种调度方法的异同．     

基于离差的区间二元语义多属性群决策方法

针对具有多粒度区间语言评价信息的多属性群决策问题,提出一种基于区间二元语义信息处理和离差最大化的群决策方法。该方法首先针对由基本语言评价集表示的区间二元语义信息,采用了多粒度区间语言评价信息一致化的方法;然后对属性权重信息完全未知的情形建立基于离差最大化的目标规划模型,得到一个求解属性权重的公式,从而获得相应的属性权重;再利用区间二元语义的集结算子对评价信息进行加权集成,通过区间二元语义信息的可能度公式对集成结果进行排序和择优;最后由实例分析说明该方法的有效性和可行性。